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Comparative Study in Classification of Dry Beans through Multilayer Perceptrons and Support Vector Machines.

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vighnesh32/Neural-Computing-Project

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Neural-Computing-Project

File Name and Description :

  1. final_models - Pickle form of the final models.
  2. pickle_files - Required pickle files for the test file.
  3. test - It is a test file in which the code can be run directly.
  4. testing_data - It is test data.
  5. project.ipynb - Python code of EDA, data visualization, partition of original data set into train and test sets, multilayer perceptron training and testing, support vector machine training and testing and hyperparameter optimization.
  6. Dry_Bean_Dataset.xlsx - Original data set.
  7. report.pdf - Project report.

Sequence for running the codes:

  1. Open and run the file project.ipynb for visualization, training and testing the models.

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Comparative Study in Classification of Dry Beans through Multilayer Perceptrons and Support Vector Machines.

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